10 papers
CRUISE: Vision-Language Model-Guided Uncertainty-Aware Cross-Modal Sensor Fusion for Robust Autonomous Driving
Junyao Wang, Yulin Xu, Yu Li +2
Modern autonomous vehicles are equipped with multiple sensors, such as cameras, LiDAR, and radar, for comprehensive environmental perception. However, robust cross-modal feature fu…
Edge Physical AI Deployment of Vision Transformers on Heterogeneous Edge GPU Targeting Autonomous Vehicles
Ashiyana Abdul Majeed, Mahmoud Meribout, Neethu Joseph +2
Physical AI systems, such as autonomous vehicles and intelligent machines, require transformer-based perception models that satisfy stringent edge latency and energy constraints. H…
HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
Luke Chen, Cheng-Ju Wu, David R. Martin +3
Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent…
RampoNN: A Reachability-Guided System Falsification for Efficient Cyber-Kinetic Vulnerability Detection
Kohei Tsujio, Mohammad Abdullah Al Faruque, Yasser Shoukry
Detecting kinetic vulnerabilities in Cyber-Physical Systems (CPS), vulnerabilities in control code that can precipitate hazardous physical consequences, is a critical challenge. Th…
Radiance Field Delta Video Compression in Edge-Enabled Vehicular Metaverse
Matúš Dopiriak, Eugen Šlapak, Juraj Gazda +3
Connected and autonomous vehicles (CAVs) offload computationally intensive tasks to multi-access edge computing (MEC) servers via vehicle-to-infrastructure (V2I) communication, ena…
Hyperdimensional Uncertainty Quantification for Multimodal Uncertainty Fusion in Autonomous Vehicles Perception
Luke Chen, Junyao Wang, Trier Mortlock +2
Uncertainty Quantification (UQ) is crucial for ensuring the reliability of machine learning models deployed in real-world autonomous systems. However, existing approaches typically…